Longhua Hospital Affiliated to Shanghai University of TCM, Shanghai 200032, China.
Comput Math Methods Med. 2013;2013:971272. doi: 10.1155/2013/971272. Epub 2013 Oct 30.
Research on core and effective formulae (CEF) does not only summarize traditional Chinese medicine (TCM) treatment experience, it also helps to reveal the underlying knowledge in the formulation of a TCM prescription. In this paper, CEF discovery from tumor clinical data is discussed. The concepts of confidence, support, and effectiveness of the CEF are defined. Genetic algorithm (GA) is applied to find the CEF from a lung cancer dataset with 595 records from 161 patients. The results had 9 CEF with positive fitness values with 15 distinct herbs. The CEF have all had relative high average confidence and support. A herb-herb network was constructed and it shows that all the herbs in CEF are core herbs. The dataset was divided into CEF group and non-CEF group. The effective proportions of former group are significantly greater than those of latter group. A Synergy index (SI) was defined to evaluate the interaction between two herbs. There were 4 pairs of herbs with high SI values to indicate the synergy between the herbs. All the results agreed with the TCM theory, which demonstrates the feasibility of our approach.
基于核心有效公式（CEF）的研究不仅可以总结中医治疗经验，还可以帮助揭示中医方剂配方中的潜在知识。本文讨论了从肿瘤临床数据中发现的 CEF。定义了 CEF 的置信度、支持度和有效性的概念。应用遗传算法（GA）从 161 名患者的 595 个记录的肺癌数据集发现了 9 个具有阳性适应度值的 CEF，共涉及 15 种不同的草药。CEF 的平均置信度和支持度都很高。构建了一个草药-草药网络，显示 CEF 中的所有草药都是核心草药。将数据集分为 CEF 组和非 CEF 组。前者的有效比例明显大于后者。定义了协同指数（SI）来评估两种草药之间的相互作用。有 4 对草药具有高 SI 值，表明这两种草药之间存在协同作用。所有结果都与中医理论相符，这证明了我们方法的可行性。
